Jay Gopalakrishnan

5.6k total citations · 1 hit paper
86 papers, 3.5k citations indexed

About

Jay Gopalakrishnan is a scholar working on Computational Mechanics, Electrical and Electronic Engineering and Mechanics of Materials. According to data from OpenAlex, Jay Gopalakrishnan has authored 86 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 67 papers in Computational Mechanics, 43 papers in Electrical and Electronic Engineering and 34 papers in Mechanics of Materials. Recurrent topics in Jay Gopalakrishnan's work include Advanced Numerical Methods in Computational Mathematics (64 papers), Electromagnetic Simulation and Numerical Methods (37 papers) and Numerical methods in engineering (31 papers). Jay Gopalakrishnan is often cited by papers focused on Advanced Numerical Methods in Computational Mathematics (64 papers), Electromagnetic Simulation and Numerical Methods (37 papers) and Numerical methods in engineering (31 papers). Jay Gopalakrishnan collaborates with scholars based in United States, Germany and Chile. Jay Gopalakrishnan's co-authors include Bernardo Cockburn, Raytcho Lazarov, Leszek Demkowicz, Joseph E. Pasciak, Guido Kanschat, L. Demkowicz, Johnny Guzmán, Weifeng Qiu, Carsten Carstensen and Antti H. Niemi and has published in prestigious journals such as Journal of Geophysical Research Atmospheres, Journal of Computational Physics and Optics Express.

In The Last Decade

Jay Gopalakrishnan

79 papers receiving 3.3k citations

Hit Papers

Unified Hybridization of Discontinuous Galerkin, Mixed, a... 2009 2026 2014 2020 2009 250 500 750

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jay Gopalakrishnan United States 31 3.1k 1.4k 1.3k 1.2k 686 86 3.5k
Dominik Schötzau Canada 37 3.9k 1.3× 1.4k 1.0× 1.4k 1.1× 1.4k 1.2× 1.5k 2.1× 81 4.5k
Pavel Bochev United States 29 2.7k 0.9× 1.2k 0.8× 658 0.5× 800 0.7× 485 0.7× 116 3.3k
Daniele Boffi Italy 25 2.8k 0.9× 1.5k 1.1× 899 0.7× 1.1k 0.9× 311 0.5× 97 3.4k
Ilaria Perugia Italy 27 2.2k 0.7× 1.2k 0.9× 1.4k 1.1× 867 0.8× 549 0.8× 78 2.8k
A. Russo Italy 34 4.9k 1.6× 3.0k 2.1× 1.4k 1.1× 2.1k 1.8× 714 1.0× 113 5.7k
Zhiqiang Cai United States 28 3.1k 1.0× 1.8k 1.2× 802 0.6× 1.3k 1.2× 455 0.7× 97 3.4k
Christine Bernardi France 29 3.0k 1.0× 1.6k 1.1× 792 0.6× 1.7k 1.5× 524 0.8× 143 3.7k
Shangyou Zhang United States 24 3.1k 1.0× 1.7k 1.2× 932 0.7× 1.4k 1.2× 575 0.8× 179 3.4k
Daniele A. Di Pietro France 27 2.9k 0.9× 1.1k 0.8× 629 0.5× 905 0.8× 635 0.9× 96 3.2k
Mats G. Larson Sweden 31 3.4k 1.1× 2.1k 1.5× 777 0.6× 1.3k 1.1× 389 0.6× 123 4.1k

Countries citing papers authored by Jay Gopalakrishnan

Since Specialization
Citations

This map shows the geographic impact of Jay Gopalakrishnan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jay Gopalakrishnan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jay Gopalakrishnan more than expected).

Fields of papers citing papers by Jay Gopalakrishnan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jay Gopalakrishnan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jay Gopalakrishnan. The network helps show where Jay Gopalakrishnan may publish in the future.

Co-authorship network of co-authors of Jay Gopalakrishnan

This figure shows the co-authorship network connecting the top 25 collaborators of Jay Gopalakrishnan. A scholar is included among the top collaborators of Jay Gopalakrishnan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jay Gopalakrishnan. Jay Gopalakrishnan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gopalakrishnan, Jay, et al.. (2025). The Johnson–Křížek–Mercier elasticity element in higher dimensions. Journal of Numerical Mathematics.
2.
Gopalakrishnan, Jay, et al.. (2023). Divergence-Conforming Velocity and Vorticity Approximations for Incompressible Fluids Obtained with Minimal Facet Coupling. Journal of Scientific Computing. 95(3). 91–91. 4 indexed citations
3.
Gopalakrishnan, Jay, et al.. (2023). Discrete elasticity exact sequences on Worsey–Farin splits. ESAIM. Mathematical modelling and numerical analysis. 57(6). 3373–3402. 1 indexed citations
4.
Gopalakrishnan, Jay, et al.. (2023). Analysis of curvature approximations via covariant curl and incompatibility for Regge metrics. PDXScholar (Portland State University). 9. 151–195. 3 indexed citations
5.
Christiansen, Snorre H., Jay Gopalakrishnan, Johnny Guzmán, & Kaibo Hu. (2023). A discrete elasticity complex on three-dimensional Alfeld splits. Numerische Mathematik. 156(1). 159–204. 7 indexed citations
6.
Gopalakrishnan, Jay, et al.. (2018). Dispersion Analysis of HDG Methods. Journal of Scientific Computing. 77(3). 1703–1735. 5 indexed citations
7.
Gopalakrishnan, Jay, et al.. (2017). A spacetime DPG method for acoustic waves. arXiv (Cornell University). 6 indexed citations
8.
Gopalakrishnan, Jay, et al.. (2017). Reduced test spaces for DPG methods using rectangular elements. Computers & Mathematics with Applications. 74(8). 1955–1963. 1 indexed citations
9.
Carstensen, Carsten, Leszek Demkowicz, & Jay Gopalakrishnan. (2016). Breaking spaces and forms for the DPG method and applications including Maxwell equations. Computers & Mathematics with Applications. 72(3). 494–522. 87 indexed citations
10.
Gopalakrishnan, Jay, et al.. (2015). A tent pitching scheme motivated by Friedrichs theory. Computers & Mathematics with Applications. 70(5). 1114–1135. 10 indexed citations
11.
Komarova, Svetlana V., et al.. (2015). Mathematical model for bone mineralization. Frontiers in Cell and Developmental Biology. 3. 51–51. 24 indexed citations
12.
Bochev, Pavel, Leszek Demkowicz, Jay Gopalakrishnan, & Max Gunzburger. (2014). Minimum Residual and Least Squares Finite Element Methods. Computers & Mathematics with Applications. 68(11). 1479–1479.
13.
Leenheer, Patrick De, et al.. (2011). Pattern formation in a generalized Keller-Segel model. arXiv (Cornell University).
14.
Cockburn, Bernardo, Jay Gopalakrishnan, & Johnny Guzmán. (2010). A new elasticity element made for enforcing weak stress symmetry. Mathematics of Computation. 79(271). 1331–1349. 83 indexed citations
15.
Muga, Ignacio, et al.. (2010). A class of discontinuous Petrov–Galerkin methods. Part IV: The optimal test norm and time-harmonic wave propagation in 1D. Journal of Computational Physics. 230(7). 2406–2432. 79 indexed citations
16.
Gopalakrishnan, Jay, et al.. (2009). A convergent multigrid cycle for the hybridized mixed method. Numerical Linear Algebra with Applications. 16(9). 689–714. 18 indexed citations
17.
Gopalakrishnan, Jay, Luis E. García-Castillo, & Leszek Demkowicz. (2005). Nédélec spaces in affine coordinates. Computers & Mathematics with Applications. 49(7-8). 1285–1294. 33 indexed citations
18.
Cockburn, Bernardo & Jay Gopalakrishnan. (2005). Incompressible Finite Elements via Hybridization. Part I: The Stokes System in Two Space Dimensions. SIAM Journal on Numerical Analysis. 43(4). 1627–1650. 56 indexed citations
19.
Gopalakrishnan, Jay & Leszek Demkowicz. (2004). Quasioptimality of some spectral mixed methods. Journal of Computational and Applied Mathematics. 167(1). 163–182. 13 indexed citations
20.
Gopalakrishnan, Jay. (2002). A Mathematical Model for Irrigated Epicardial Radiofrequency Ablation. Annals of Biomedical Engineering. 30(7). 884–893. 25 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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